A questionnaire that clinicians can administer in 20 minutes, either in person, by phone or online, correctly distinguishes children with autism from those without the disorder 86 percent of the time. Researchers described the tool 15 July in the Journal of Child Psychology and Psychiatry1.
The ‘gold-standard’ diagnostic tools for autism are the Autism Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R). Both of these tools require extensive training to use and take hours to implement, making them impractical for use on a large scale or by clinicians who don’t specialize in autism.
In the new study, researchers tested an autism module of the Development and Well-Being Assessment (DAWBA) — a questionnaire developed to assess children for psychiatric disorders. The autism module, which is still being validated, probes a child’s attachment to certain adults, stress levels during social situations and need for rituals. Parents, teachers or the child himself can respond to the questions. A computer algorithm then analyzes the results and calculates the child’s likelihood of having autism.
...The DAWBA correctly flagged 88 percent of children who met the criteria for autism on the ADOS and the ADI-R. It also accurately identified children without the disorder 87 percent of the time. This means that it missed 12 percent of children with autism, and incorrectly pegged 13 percent of children as having autism — error rates on par with those of similar tools that require more intensive training to use, the researchers say.
The DAWBA could serve as a quick follow-up to autism screening tools, such as the Childhood Autism Spectrum Test (CAST) or the Social Communication Questionnaire. These tools are typically used in schools and pediatricians' offices to see if more specialized tests, such as the ADOS or ADI-R, are warranted.From the abstract:
Increasing numbers of people are being referred for the assessment of autism spectrum disorder (ASD). The NICE (UK) and the American Academy of Pediatrics recommend gathering a developmental history using a tool that operationalises ICD/DSM criteria. However, the best-established diagnostic interview instruments are time consuming, costly and rarely used outside national specialist centres. What is needed is a brief, cost-effective measure validated in community settings. We tested the Development and Well-Being Assessment (DAWBA) for diagnosing ASD in a sample of children/adolescents representative of those presenting in community mental health settings.
The DAWBA is a brief structured interview that showed good sensitivity and specificity in this general population sample. It requires little training, is easy to administer (online or by interview) and diagnosis is aided by an algorithm. It holds promise as a tool for assisting with assessment in community settings and may help services implement the recommendations made by NICE and the American Academy of Pediatrics regarding diagnosis of young people on the autism spectrum.